“Erring on the side of least drama” — Why climate scientists are inherently conservative (video)

I’ve been writing for a while that predictions from climate scientists are consistently “wrong to the slow side” — a statement that, if true, adds even greater urgency to stopping carbon emissions.

My favorite “wrong to the slow side” graphic is from the Copenhagen Diagnosis, the climate document produced ahead of the 2009 summit in Copenhagen. It shows loss of Arctic summer ice, both modeled and observed. In other words, IPCC models were run that showed the likely range of loss of Arctic summer ice, year by year, and over that, the actual, observed loss for the same time period was shown. As the accompanying caption says:

Observed (red line) and modeled September Arctic sea ice extent in millions of square kilometers. The solid black line gives the ensemble mean of the 13 IPCC AR4 models while the dashed black lines represent their range.

“AR4” is the 2007 IPCC Assessment Report 4, the most recent at the time. Here’s that figure:

See what I mean? Wrong to the slow side. Arctic ice is disappearing fast.

Scientists tend to “err on the side of least drama”

There are many examples of the above, where models are more conservative than observations and tend to “under-predict.” In addition, scientists also tend to throw away the more extreme conclusions (or most “dramatic,” as you’ll see below), even when those extreme conclusions are also the most likely.

Why is that? History of Science professor Naomi Oreskes has studied that phenomenon. In a 2012 peer-reviewed paper, “Climate change prediction: Erring on the side of least drama?” (pdf), she and her colleagues put to the test the claim of climate deniers that “climate scientists are alarmists.” When they tested that conclusion by looking at actual data — climate projections and how they compare to climate outcomes — they discovered something very interesting. In fact, the opposite is true. Climate scientists tend to underplay their results.

Here’s Dr. Oreskes in a short video to explain. When she says “this particular piece of work” at the beginning, she’s referring to the 2012 paper I mentioned above, then in preparation.

The source of this interview is this entry in the American Geophysical Union blog. The writer, Dan Satterfield, has interesting comments of his own as well.

As Dr. Oreskes says in introducing her main point (my emphasis):

“What we’re proposing is that the core values of science, the core values of the scientific community — rationality, objectivity, dispassion, restraint, moderation — actually introduce a bias into scientific evaluation in cases where some possible outcomes are, in fact, dramatic.

“And that when scientists encounter outcomes that are potentially quite dramatic — or even potentially alarming — that it actually makes them uncomfortable. And they have a tendency, and I would argue subconsciously, to emphasize the more cautious range of their data, erring on the side of least drama. Erring on the side of the data that seems less dramatic and less alarming.

“The argument of the paper is that, this is really a problem, a source of bias.”

More than a “source of bias,” I would argue. For a situation this serious to be this underplayed is genuinely dangerous.

The evidence

The evidence in the paper is compelling. The link is here (pdf); note that the annotation was added by the hosting site and is not part of the original. For example, from a 2007 paper by Rahmstorf et al, Oreskes and her colleagues write (my emphasis and some reparagraphing everywhere):

In a 2007 article, Rahmstorf and colleagues compared projections of global mean temperature change, sea level rise, and atmospheric carbon dioxide concentration from IPCC’s Third Assessment Report (TAR) with observations made since 1973 and concluded:

‘‘Overall, these observational data underscore the concerns about global climate change. Previous projections, as summarized by IPCC, have not exaggerated but may in some respects even have underestimated the change, in particular for sea level’’ (p. 709).

In the TAR, released in 2001, the IPCC predicted an average sea level rise of less than 2 mm/yr, but from 1993 to 2006, sea level actually rose 3.3 mm/yr—more than 50% above the IPCC prediction (Houghton et al., 2001). Furthermore, the temperature change over the period ‘‘is 0.33 8C for the 16 years since 1990, which is in the upper part of the range projected by the IPCC (in the TAR).’’ The underestimate in sea level rise can be traced in part to under-projection of ice loss from Antarctica and Greenland, as discussed in detail later in this paper.

And:

In a 2008 paper, Roger Pielke, Jr. … observed that for sea level rise, actual changes have been greater than forecast in two of three prior IPCC reports, while falling below the median prediction in the First Assessment Report (FAR).

And:

These conclusions are also supported in a report prepared by the Committee on Strategic Advice on the U.S. Climate Change Science Program [NRC, 2009] … The results of the three-year study … were consistent with the conclusion that IPCC projections have systematically underestimated key climate change drivers and impacts. … The key climate metrics of global mean temperature and sea level rise are biased toward underestimation, so far as the evidence in this analysis shows.

And from the 2009 Copenhagen Diagnosis, mentioned above:

The Copenhagen Diagnosis (Allison et al., 2009), reviewed ‘‘hundreds of papers . . . on a suite of topics related to human-induced climate change’’ since the drafting of AR4 [IPCC Assessment Report 4, 2007], and, like the NRC report, found that key changes were happening either at the same rate as, or more quickly than, anticipated (p. 5).

Among their key findings were that global temperature increases over the past 25 years have been consistent with model predictions (0.19 °C per decade, virtually the same rate as for the 16 years mentioned in Rahmstorf et al., 2007), while other important impacts are proceeding faster than expected, including CO2 emissions, increased rainfall in already rainy areas, continental ice-sheet melting, arctic sea-ice decline, and sea level rise.

The paper goes on to elaborate those findings, and then offers quite a number of other examples similar to those above — predictions of hurricane intensity and frequency, ozone depletion, ice sheet destruction, predictions of permafrost melt, and so on.

About the latter (permafrost and its melting methane), the paper observes:

The total carbon contained in permafrost [in the form of frozen methane] has been estimated at 1672 gigatons, more than twice the amount of carbon in the atmosphere (Tarnocai et al., 2009). This means that the potential amplifying effect of greenhouse gas release from permafrost melting is enormous. Yet this feedback ‘‘has not been accounted for in any of the IPCC projections’’ (Allison et al., 2009, p. 21). This omission introduces a potentially profound bias in the climate projections—not toward overestimation of climate change, but toward its underestimation.

I’ve written about methane here, and will write more as we look into James Hansen’s work on climate sensitivity — how responsive our climate system is to destabilizing influences — and slower amplifying feedbacks like permafrost melt. Oreskes and her colleagues are right that, through 2009, the IPCC hasn’t included the feedback from melting methane in their projections — partly because it’s hard to model and partly because the conclusions tend to be extreme (if you click, note McPherson’s comments).

Climate sensitivity and “extreme” results

As an example of those “extreme” results, consider this, from something I’m working on now. In general, “climate sensitivity” is an attempt to quantify how much earth’s climate system reacts to stimulus. Do quantified changes in stimulus (more CO2, for example, or increased radiation by the sun) produce large temperature changes, or smaller ones?

The standard measure of “climate sensitivity,” one which includes only fast and easily modeled feedbacks — water vapor, clouds, volcanic dust and so on — says that if you would instantly double atmospheric CO2 in ppm (parts per million) — a known amount of “forcing” — global temperature would increase +3°C before it restabilizes. In other words, by this measure, “climate sensitivity” is “3°C”. That number for sensitivity is widely used; you see it in Michael Mann’s recent work, for instance (the link is to my write-up).

NASA’s James Hansen, however, has convincingly shown (pdf) that the real sensitivity number is low by as much as half if you also include slow feedbacks like loss of reflective sea ice and, yes, melted Arctic methane. To make that real — if Hansen is right and we succeed in doubling atmospheric CO2 from the stable pre-industrial level of 280 ppm to 560 ppm, and then stop, we could well have handed ourselves +6°C global warming, guaranteed, after restabilization. 6°C warmer is a world before any glaciers formed, more than 50 million years ago.

We’re at roughly 400 ppm now, and emissions are accelerating. How long before we get to 560 ppm? If we keep going like this, it happens this century. “Extreme” results.

Causes of “conservative bias” in climate pronouncements

Oreskes nicely explains in the video most of the causes of “erring on the side of least drama.” One cause she doesn’t emphasize above — but does treat in the paper — is the constant hammering scientists are subjected to, especially in the U.S., by the well-funded denialist machine (my phrasing).

Oreskes (again, my emphasis and paragraphing):

Given the challenging political environment in which climate scientists operate, and the fact that climate scientists have been repeatedly accused of fear-mongering and alarmism, we might conclude that scientific reticence with respect to global warming is a consequence of the charged political context in which climate scientists operate.

Freudenberg and Muselli (2010) have suggested that the asymmetry of political pressure, particularly in the United States, has contributed to a conservative bias in IPCC assessments. These authors emphasize that most analyses of scientific communication focus on the flow (and impact) of information from scientists to the larger public, paying far less attention to the reverse flow—in this case, the strongly stated criticism of scientists by contrarians and skeptics, widely repeated in the North American press, and then spread more widely on the internet.

They suggest that this reverse flow [of information back to climate scientists] has contributed to a bias in which scientists not only bend over backward to ensure that their results are absolutely warranted by the evidence, but actually take positions that are more conservative than warranted by the evidence to disprove contrarian accusations of scientific ‘‘alarmism.’’

I’ll leave you to check out the rest of this fine work. I found the paper fascinating. Again, it’s data-driven and peer-reviewed. This is not just someone making an “eyeball” estimate.

And I’ll say this about the billionaires — the David Kochs and other deep-pocket funders of our collective lemming-walk to the cliff — they’re definitely getting their money’s worth. Those denial dollars have bought a lot of time. It’s down to just a few more years as I see it. Time to make a strong move for our side.